Smartphone Clustering for Energy-Efficient Group Tracking
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Solution Overview
Problem
Existing group tracking systems consume high energy and rapidly deplete battery life when tracking individuals using real-time GPS information, and they lack efficiency in accurately locating travelers while monitoring their safety and progress.
Innovation Solution
A smartphone clustering method where each smartphone identifies neighboring devices, determines a cluster head, and transmits personal information via near-field communication, allowing the cluster head to aggregate and transmit position and personal data to a server, reducing the energy burden on individual devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual GPS tracking is used for each smartphone in the group, then real-time location accuracy is improved, but energy consumption increases and battery life decreases
Solution Approach 1:
The system divides the tracking function into two segments: (1) individual smartphones perform near-field communication to share location data with neighbors, and (2) a designated cluster head performs GPS positioning and aggregates data for server transmission. This segmentation allows most devices to avoid continuous GPS usage while maintaining group tracking accuracy.
Solution Approach 2:
The cluster head acts as an intermediary between individual smartphones and the server. It collects location information from neighboring smartphones via near-field communication, performs GPS positioning itself, and transmits aggregated data to the server. This intermediary role eliminates the need for every device to perform energy-intensive GPS operations.
2Measurement precision
If continuous GPS positioning is performed by all smartphones, then real-time tracking accuracy is improved, but battery life is rapidly depleted
Solution Approach 1:
The tracking function is segmented so that only the cluster head performs continuous GPS positioning, while other smartphones use lower-power near-field communication to share their location updates. This dramatically extends battery life for non-cluster-head devices while maintaining real-time tracking accuracy through the cluster head's GPS data.
Solution Approach 2:
The system merges location data from multiple smartphones via near-field communication into a single aggregated dataset managed by the cluster head. This combining approach allows the group to maintain accurate tracking information without each device independently performing continuous GPS operations.
3Reliability
If dedicated staff are assigned to monitor all groups, then safety monitoring quality is improved, but human resource requirements increase
Solution Approach 1:
The smartphone clustering system enables groups to perform self-monitoring of their location and safety status without requiring external staff. The cluster head automatically aggregates data from all group members and transmits it to the server, which can then alert authorities if safety thresholds are violated. This self-service capability eliminates the need for dedicated monitoring staff while maintaining safety oversight.
Solution Approach 2:
The server acts as an intermediary that receives aggregated location data from multiple cluster heads and performs centralized safety monitoring. This allows the system to monitor many groups simultaneously with minimal human resources, as the server automatically processes data and triggers alerts only when safety violations occur.
Data Source
AI summary
A device, method, and non-transitory computer readable medium for using a smartphone clustering application. The method includes identifying, by each smartphone equipped with the smartphone clustering application, a cluster of neighboring smartphones equipped with the smartphone clustering application; determining a cluster head by each smartphone in the cluster; determining position by the cluster head; transmitting personal information by each smartphone to the cluster head; receiving the personal information from each of the neighboring smartphones by the cluster head; aggregating personal information with the personal information from each of the neighboring smartphones by the cluster head and generating aggregated personal information; combining, by the cluster head, its position with the aggregated personal information into a communication stream; identifying an access point by the cluster head; transmitting the communication stream to the access point; and transmitting the communication stream by the access point to a server side smartphone clustering application.